Social Dimensions and Processes in Second Language Acquisition: Multilingual Socialization in Transnational Contexts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Social aspects of second language acquisition (SLA) and the contexts in which people attempt to learn and use languages and seek to become integrated within new and changing cultures have been examined for decades from various theoretical perspectives. In this article, I present some of the ways in which ‘social’ experience is being theorized in SLA and in broader fields that intersect with SLA, such as linguistic anthropology. I then discuss how the Douglas Fir Group (DFG, 2016) originally portrayed the many interlinking factors affecting SLA in our multilingual world on several analytic levels and suggest ways of perhaps reconceptualizing the model while retaining its powerful heuristic value. Next, I describe language socialization research as 1 productive social approach and provide examples of research in 2 transnational domains—study abroad and heritage language learning—that demonstrate a multiscalar approach to examining social dimensions of language development and use. The article ends with a discussion of transdisciplinarity in SLA research. I suggest possibilities for team‐based research projects that aim to understand cases from multiple, integrated perspectives on different scales of analysis, and then provide a brief reflection on some of the troubling political ideologies that SLA researchers who embrace multilingualism must now confront on a daily basis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it